Genetically engineered bacteria have the potential to diagnose and treat a wide range of diseases linked to the gastrointestinal tract, or gut. Such engineered microbes will be less expensive and invasive than current diagnostics and more effective and safe than current therapeutics. Recent advances in synthetic biology have dramatically improved the reliability with which bacteria can be engineered with the sensors, genetic circuits, and output (actuator) genes necessary for diagnostic and therapeutic functions. However, to deploy such bacteria in vivo, researchers must identify appropriate gut-adapted strains and consider performance metrics such as sensor detection thresholds, circuit computation speed, growth rate effects, and the evolutionary stability of engineered genetic systems. Other recent reviews have focused on engineering bacteria to target cancer or genetically modifying the endogenous gut microbiota in situ. Here, we develop a standard approach for engineering “smart probiotics,” which both diagnose and treat disease, as well as “diagnostic gut bacteria” and “drug factory probiotics,” which perform only the former and latter function, respectively. We focus on the use of cutting-edge synthetic biology tools, gut-specific design considerations, and current and future engineering challenges.

Genetically engineered bacteria have the potential to diagnose and treat a wide range of diseases linked to the gastrointestinal tract, or gut. Such engineered microbes will be less expensive and invasive than current diagnostics and more effective and safe than current therapeutics. Recent advances in synthetic biology have dramatically improved the reliability with which bacteria can be engineered with the sensors, genetic circuits, and output (actuator) genes necessary for diagnostic and therapeutic functions. However, to deploy such bacteria in vivo, researchers must identify appropriate gut-adapted strains and consider performance metrics such as sensor detection thresholds, circuit computation speed, growth rate effects, and the evolutionary stability of engineered genetic systems. Other recent reviews have focused on engineering bacteria to target cancer or genetically modifying the endogenous gut microbiota in situ. Here, we develop a standard approach for engineering “smart probiotics,” which both diagnose and treat disease, as well as “diagnostic gut bacteria” and “drug factory probiotics,” which perform only the former and latter function, respectively. We focus on the use of cutting-edge synthetic biology tools, gut-specific design considerations, and current and future engineering challenges.

The three classes of engineered gut bacteria. Smart probiotics sense one or more biomarkers, compute that those biomarkers are present in a combination indicative of disease, and respond by delivering a precise dose of one or more appropriate therapeutics at the diseased tissue. Diagnostic gut bacteria sense one or more biomarkers, compute that those biomarkers are present in a combination indicative of disease, and produce a reporter which can be externally measured by a clinician. Drug factory probiotics constitutively produce a therapeutic within the body.

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FIGURE 1

The three classes of engineered gut bacteria. Smart probiotics sense one or more biomarkers, compute that those biomarkers are present in a combination indicative of disease, and respond by delivering a precise dose of one or more appropriate therapeutics at the diseased tissue. Diagnostic gut bacteria sense one or more biomarkers, compute that those biomarkers are present in a combination indicative of disease, and produce a reporter which can be externally measured by a clinician. Drug factory probiotics constitutively produce a therapeutic within the body.

A comparison of the development process for natural and engineered probiotics. (A) Natural probiotics are isolated and then tested for efficacy without an ability to methodically improve their capabilities. (B) In contrast, engineered probiotics undergo a design-build-test-learn cycle which allows for continual probiotic improvement and knowledge gain with each iteration.

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FIGURE 2

A comparison of the development process for natural and engineered probiotics. (A) Natural probiotics are isolated and then tested for efficacy without an ability to methodically improve their capabilities. (B) In contrast, engineered probiotics undergo a design-build-test-learn cycle which allows for continual probiotic improvement and knowledge gain with each iteration.

Examples of current engineered gut bacteria. (A) A drug factory probiotic was made by engineering L. lactis to constitutively produce IL-10. IL-10 is secreted by the bacteria and then bound by the IL-10 receptor in the gut, resulting in downregulation of host inflammation. (B) DSS was used to induce inflammation in mice, and disease pathology was measured with histological scores. Treatment with the IL-10 drug factory probiotic was found to decrease symptoms by 50% compared to untreated mice or mice administered the natural probiotic L. lactis. (C) A diagnostic gut bacterium was created by engineering E. coli Nissle to sense thiosulfate, which is produced in the gut during inflammation. The thiosulfate is sensed by the ttrSR TCS, which activates expression of the fluorescent protein sfGFP. (D) sfGFP fluorescence of bacteria isolated from the feces and distal and proximal colon was measured and found to be significantly increased in mice experiencing inflammation in each location. Panel adapted from Mol Syst Biol (55) with permission of the publisher. (E)E. coli NGF-1 was modified to express the ATC sensor TetR, which controlled expression of the cro TF. The cro TF is one component of the lambda phage cro/cI toggle switch. ATC altered the start of the switch to become cro-dominant, and therefore produce LacZ protein, which produces a blue pigment. (F) The ATC-sensing diagnostic gut bacteria were administered to mice which were administered ATC via drinking water. Temporary administration of ATC was found to activate LacZ production, and the memory was retained for up to 1 week. Panel adapted from Proceedings of the National Academy of Sciences (56) with permission of the publisher. (G) The native RhaR rhamnose sensor in B. thetaiotaomicron was used to control expression of the Int12 recombinase, which permanently inverts a barcode segment of DNA in the genome. (H) The rhamnose diagnostic gut bacteria switched the state of the barcode as detected via qPCR when administered rhamnose in drinking water. However, even without administration of rhamnose, the sensor toggled states, due to either leaky recombination or residual rhamnose in the plant-based chow. Panel reprinted from Cell Systems (51) with permission of the publisher.

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FIGURE 3

Examples of current engineered gut bacteria. (A) A drug factory probiotic was made by engineering L. lactis to constitutively produce IL-10. IL-10 is secreted by the bacteria and then bound by the IL-10 receptor in the gut, resulting in downregulation of host inflammation. (B) DSS was used to induce inflammation in mice, and disease pathology was measured with histological scores. Treatment with the IL-10 drug factory probiotic was found to decrease symptoms by 50% compared to untreated mice or mice administered the natural probiotic L. lactis. (C) A diagnostic gut bacterium was created by engineering E. coli Nissle to sense thiosulfate, which is produced in the gut during inflammation. The thiosulfate is sensed by the ttrSR TCS, which activates expression of the fluorescent protein sfGFP. (D) sfGFP fluorescence of bacteria isolated from the feces and distal and proximal colon was measured and found to be significantly increased in mice experiencing inflammation in each location. Panel adapted from Mol Syst Biol (55) with permission of the publisher. (E)E. coli NGF-1 was modified to express the ATC sensor TetR, which controlled expression of the cro TF. The cro TF is one component of the lambda phage cro/cI toggle switch. ATC altered the start of the switch to become cro-dominant, and therefore produce LacZ protein, which produces a blue pigment. (F) The ATC-sensing diagnostic gut bacteria were administered to mice which were administered ATC via drinking water. Temporary administration of ATC was found to activate LacZ production, and the memory was retained for up to 1 week. Panel adapted from Proceedings of the National Academy of Sciences (56) with permission of the publisher. (G) The native RhaR rhamnose sensor in B. thetaiotaomicron was used to control expression of the Int12 recombinase, which permanently inverts a barcode segment of DNA in the genome. (H) The rhamnose diagnostic gut bacteria switched the state of the barcode as detected via qPCR when administered rhamnose in drinking water. However, even without administration of rhamnose, the sensor toggled states, due to either leaky recombination or residual rhamnose in the plant-based chow. Panel reprinted from Cell Systems (51) with permission of the publisher.

An outline of the types of sense, compute, and respond behavior an engineered gut bacterium can exhibit. Chemicals from a variety of sources within the gut may be of interest to a smart bacterium, including the host diet, compounds produced locally by the host in the bacterium’s microenvironment, signals from other components of the microbiome, and general biomarkers of host disease. Computation is performed with a variety of logic gates and memory elements. The bacterium actuates a response with a therapeutic molecule in the case of a smart probiotic, or by producing a nucleotide or protein-based reporter for a diagnostic gut bacterium.

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FIGURE 4

An outline of the types of sense, compute, and respond behavior an engineered gut bacterium can exhibit. Chemicals from a variety of sources within the gut may be of interest to a smart bacterium, including the host diet, compounds produced locally by the host in the bacterium’s microenvironment, signals from other components of the microbiome, and general biomarkers of host disease. Computation is performed with a variety of logic gates and memory elements. The bacterium actuates a response with a therapeutic molecule in the case of a smart probiotic, or by producing a nucleotide or protein-based reporter for a diagnostic gut bacterium.

The different components used to construct an engineered gut bacterium. The pros and cons of each component are listed in green and red text, respectively. (A) Sensors can be selected from OCSs or TCSs. (B) Logic circuits can be constructed using TFs, CRISPR/Cas repressors, RNA-based sRNA transcriptional activators, or serine recombinases. (C) Genetic memory can take the form of a toggle switch or recombined DNA. (D) The state of a circuit can be assayed using colorimetric, luminescent, fluorescent, or nucleotide reporters.

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FIGURE 5

The different components used to construct an engineered gut bacterium. The pros and cons of each component are listed in green and red text, respectively. (A) Sensors can be selected from OCSs or TCSs. (B) Logic circuits can be constructed using TFs, CRISPR/Cas repressors, RNA-based sRNA transcriptional activators, or serine recombinases. (C) Genetic memory can take the form of a toggle switch or recombined DNA. (D) The state of a circuit can be assayed using colorimetric, luminescent, fluorescent, or nucleotide reporters.